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About

Dollaporn Anopas is a researcher at the forefront of neurorehabilitation robotics, specializing in the intersection of spinal cord injury (SCI) recovery, robotic assistance, and machine learning. Her work focuses on developing intelligent systems to restore natural locomotion in both animal models and human patients. Anopas’s major contribution is the creation of a developmental rehabilitation robotic system for rats with complete thoracic SCI, enabling quadruped posture training to promote axonal regeneration—a foundational study with 10 citations. She has also pioneered unsupervised learning techniques for real-time gait phase detection, moving beyond handcrafted features to extract phase information from repetitive movements, with her 2018 paper on this topic garnering 8 citations. Her recent 2024 work advances this by enabling continuous, real-time gait phase detection for stroke and SCI patients, addressing a critical gap in robotic rehabilitation. Additionally, Anopas has developed methods to automatically infer and synchronize hindlimb trajectories with forelimb gait in spinalized rats, a key step toward simulating natural walking patterns. Her research, supported by publications in top venues, is driving the next generation of adaptive, data-driven rehabilitation robotics.